@phdthesis{Geissendoerfer2024,
  author    = {Geißend{\"o}rfer, Lisa},
  title     = {The Macroeconomic Dimensions of Credit: A Comprehensive Analysis of Finance, Inequality and Growth},
  doi       = {10.25972/OPUS-37003},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-370037},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Besonders einflussreich f{\"u}r das moderne Verst{\"a}ndnis zur makro{\"o}konomischen Rolle von Banken und Kredit ist die monet{\"a}re Wachstumstheorie von Schumpeter. Ausgehend von dieser wird in dieser Dissertation die makro{\"o}konomische Rolle des Finanzsystems f{\"u}r die (1) Erzeugung von Wirtschaftswachstum, (2) Lenkung von {\"o}konomischen Ressourcen und (3) Verteilung von Wohlstand untersucht. In Kapitel 3 wird zun{\"a}chst empirisch gezeigt, dass 1.) ein positiver Zusammenhang zwischen dem Wachstum von Krediten und Wirtschaftswachstum besteht, auch f{\"u}r entwickelte L{\"a}nder, 2.) kein empirischer Zusammenhang von Haushaltssparen und Wirtschaftswachstum festgestellt werden kann, und 3.) auf l{\"a}nderspezifischer Ebene sowohl positive, als auch negative und insignifikante Effekte von Kredit auf Wirtschaftswachstum existieren. Damit zeigt sich eine breite empirische Evidenz f{\"u}r Schumpeters monet{\"a}re Hypothesen. Eine besonders interessante Anwendung von Schumpeters Wachstumstheorie zeigt sich in China. Die Ergebnisse der empirischen Analyse legen nahe, dass es generell einen positiven Zusammenhang zwischen Kredit- und Wirtschaftswachstum in China gibt, der aber nicht linear in Bezug auf Regionen, Zeitpunkte und Gr{\"o}ße des Finanzsystems ist. Weiterhin deuten die Ergebnisse darauf hin, dass die kreditfinanzierte Industriepolitik in China zu mehr Investitionen und BIP-Wachstum beigetragen haben k{\"o}nnte, wobei es jedoch Nichtlinearit{\"a}ten zwischen einzelnen Branchen und Unternehmenstypen gibt. Zuletzt wird in Kapitel 5 die Frage aufgeworfen, welche Rolle das Finanzsystem bei der Verteilung des Wohlstands spielt. W{\"a}hrend Kredite an Haushalte und Unternehmen, zusammen mit Indikatoren zum Arbeits- und Sparverhalten, sowie zur Altersstruktur der Bev{\"o}lkerung, die wichtigsten Determinanten von Verm{\"o}gensungleichheit sind, zeigen sich in der Beziehung von Krediten und Verm{\"o}gensungleichheit ebenfalls verschiedene Nichtlinearit{\"a}ten, u.a. im Bezug auf den Entwicklungsstand von Finanzsystemen und Wohneigentumsquoten.},
  subject      = {Kredit},
  language  = {en}
}
@techreport{BofingerGeissendoerferHaasetal.2023,
  author    = {Bofinger, Peter and Geißend{\"o}rfer, Lisa and Haas, Thomas and Mayer, Fabian},
  title     = {Credit as an Instrument for Growth: A Monetary Explanation of the Chinese Growth Story},
  doi       = {10.25972/OPUS-32880},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-328804},
  pages     = {148},
  year      = {2023},
  abstract  = {This study describes the Chinese growth model over the past 40 years. We show that China's growth model, with its dominant role of the banking system and "the banker", is a perfect illustration of the necessity and power of Schumpeter's "monetary analysis". This approach has allowed us to elaborate theoretically and empirically the uniqueness of the Chinese model. In our empirical analysis, we use a new dataset of Chinese provincial data to analyze the impact of the financial system, especially banks, on Chinese economic development. We also empirically assess the role of the financial system in Chinese industrial policy and provide case studies of the effects of industrial policy in specific sectors. Finally, we also discuss macroeconomic dimensions of the Chinese growth process and lessons that can be drawn from the Chinese experience for other countries.},
  subject      = {Industriepolitik},
  language  = {en}
}
@phdthesis{Gruendler2018,
  author    = {Gr{\"u}ndler, Klaus},
  title     = {A Contribution to the Empirics of Economic Development - The Role of Technology, Inequality, and the State},
  edition   = {1. Auflage},
  publisher = {W{\"u}rzburg University Press},
  address   = {W{\"u}rzburg},
  isbn      = {978-3-95826-072-6 (Print)},
  doi       = {10.25972/WUP-978-3-95826-073-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-141520},
  school      = {W{\"u}rzburg University Press},
  pages     = {300},
  year      = {2018},
  abstract  = {This dissertation contributes to the empirical analysis of economic development. The continuing poverty in many Sub-Saharan-African countries as well as the declining trend in growth in the advanced economies that was initiated around the turn of the millennium raises a number of new questions which have received little attention in recent empirical studies. Is culture a decisive factor for economic development? Do larger financial markets trigger positive stimuli with regard to incomes, or is the recent increase in their size in advanced economies detrimental to economic growth? What causes secular stagnation, i.e. the reduction in growth rates of the advanced economies observable over the past 20 years? What is the role of inequality in the growth process, and how do governmental attempts to equalize the income distribution affect economic development? And finally: Is the process of democratization accompanied by an increase in living standards? These are the central questions of this doctoral thesis. To facilitate the empirical analysis of the determinants of economic growth, this dissertation introduces a new method to compute classifications in the field of social sciences. The approach is based on mathematical algorithms of machine learning and pattern recognition. Whereas the construction of indices typically relies on arbitrary assumptions regarding the aggregation strategy of the underlying attributes, utilization of Support Vector Machines transfers the question of how to aggregate the individual components into a non-linear optimization problem. Following a brief overview of the theoretical models of economic growth provided in the first chapter, the second chapter illustrates the importance of culture in explaining the differences in incomes across the globe. In particular, if inhabitants have a lower average degree of risk-aversion, the implementation of new technology proceeds much faster compared with countries with a lower tendency towards risk. However, this effect depends on the legal and political framework of the countries, their average level of education, and their stage of development. The initial wealth of individuals is often not sufficient to cover the cost of investments in both education and new technologies. By providing loans, a developed financial sector may help to overcome this shortage. However, the investigations in the third chapter show that this mechanism is dependent on the development levels of the economies. In poor countries, growth of the financial sector leads to better education and higher investment levels. This effect diminishes along the development process, as intermediary activity is increasingly replaced by speculative transactions. Particularly in times of low technological innovation, an increasing financial sector has a negative impact on economic development. In fact, the world economy is currently in a phase of this kind. Since the turn of the millennium, growth rates in the advanced economies have experienced a multi-national decline, leading to an intense debate about "secular stagnation" initiated at the beginning of 2015. The fourth chapter deals with this phenomenon and shows that the growth potentials of new technologies have been gradually declining since the beginning of the 2000s. If incomes are unequally distributed, some individuals can invest less in education and technological innovations, which is why the fifth chapter identifies an overall negative effect of inequality on growth. This influence, however, depends on the development level of countries. While the negative effect is strongly pronounced in poor economies with a low degree of equality of opportunity, this influence disappears during the development process. Accordingly, redistributive polices of governments exert a growth-promoting effect in developing countries, while in advanced economies, the fostering of equal opportunities is much more decisive. The sixth chapter analyzes the growth effect of the political environment and shows that the ambiguity of earlier studies is mainly due to unsophisticated measurement of the degree of democratization. To solve this problem, the chapter introduces a new method based on mathematical algorithms of machine learning and pattern recognition. While the approach can be used for various classification problems in the field of social sciences, in this dissertation it is applied for the problem of democracy measurement. Based on different country examples, the chapter shows that the resulting SVMDI is superior to other indices in modeling the level of democracy. The subsequent empirical analysis emphasizes a significantly positive growth effect of democracy measured via SVMDI.},
  subject      = {Wirtschaftsentwicklung},
  language  = {en}
}